| 项目编号: | 1623417
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| 项目名称: | CAREER: Modeling and Optimization of Next Generation Feedstock Development for Chemical Process Industry |
| 作者: | Selen Cremaschi
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| 承担单位: | Auburn University
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| 批准年: | 2016
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| 开始日期: | 2016-01-01
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| 结束日期: | 2017-01-31
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| 资助金额: | 96308
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| 资助来源: | US-NSF
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| 项目类别: | Continuing grant
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| 国家: | US
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| 语种: | 英语
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| 特色学科分类: | Engineering - Chemical, Bioengineering, Environmental, and Transport Systems
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| 英文关键词: | biomass feedstock system
; pi
; research
; simulation-based optimization approach
; cpi
; cpi feedstock development
; technological development
; biomass feedstock conversion
; impact
; project
; evolution
; cpi feedstock
; fossil basedfeedstock
; biomass-to commodity chemical investment decision problem
; advance
; stochastic optimization problem
; new technology development
; faculty early career development
; chemical process industry
; classical chemical catalysis
; technology development
; biomass feedstock
; chemical engineering
|
| 英文摘要: | 1055974
Cremaschi
Intellectual Merit:
Biomass has great potential for weaning the chemical process industries (CPI) from fossil based
feedstocks. As a renewable and locally available resource, the use of biomass as a CPI feedstock will have a synergistic effect on the U.S. economy by supporting the agricultural sector and promoting future innovation and growth of the CPI. The switch from current fossil fuel based CPI to a future CPI that utilizes biomass feedstock will require substantial amounts of research & development (R&D) and capital investments for technology development both by the CPI and the government. There is opportunity for investigating how these investments will impact the evolution of the biomass feedstock system.
The research objective of this Faculty Early Career Development (CAREER) project is to develop novel models and computational methods that are capable of predicting the impact of R&D and capital investment decisions (how much to invest and in which technology and when) on the evolution of biomass conversion technologies for CPI feedstock development. Two characteristics of this system, uncertain decision-dependent endogenous technology evolutions and game theoretic issues, limit the applicability of existing representations and methods. Drawing analogies to the R&D pipeline management and graph theory, the PI proposes two frameworks to analyze this problem. First, the PI will investigate the effectiveness of these frameworks for the investment problem with respect to four criteria: easy scalability, universality, ability to represent the uncertain evolution paths of different technologies, and amenability to community upkeep and expansion. The PI will next develop simulation-based optimization approaches to the investment problem assuming perfect information sharing among the government and CPI agents. Lastly, the PI will develop an agent-based framework embedding simulation-based optimization approach as decision models in the agent-based framework and investigate the impact of game-theoretic issues on the investment decisions when complete information is not available to any party. This research to study the biomass-to commodity chemicals investment decision problem should lead to advances in representation of technological developments and evolution problems, large-scale solution capability of stochastic optimization problems with exogenous and endogenous uncertainties, and fundamental understanding of how game theoretic issues impact new technology development and evolution, particularly for the biomass feedstock system.
Broader Impacts:
The overarching goals of the education plan are to integrate research and education and contribute to the diversity of the engineering workforce and scientific community by training students in systems-level thinking. These goals will be achieved by:
1. Integrating research themes and projects that require and promote systems-level thinking and interdisciplinary work into traditional engineering undergraduate curriculum courses,
2. Expanding the undergraduate/graduate-level course, Risk Management and Optimization (developed by the PI) and integrating projects from this research into the course,
3. Engaging and mentoring at least two undergraduate students per year in this research project utilizing two successful unique campus wide capstone programs that promote student participation in original research programs, and
4. Recruiting and supervising at least two full time graduate students who will pursue advanced degrees in chemical engineering.
Advances in biomass feedstock conversion could lead to advances ranging from hybrid and seed engineering, to fertilizer and other agricultural techniques, to classical chemical catalysis. Because of the importance to U.S. national and economic security and the range of options available for evolving a complex biomass feedstock system, this work has potential for scientific, technical and societal impact. In addition to the dissemination of the results via scientific publications and at national and international meetings, the developed models will be made available for the use of the community through the World Wide Web. |
| 资源类型: | 项目
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/92937
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| Appears in Collections: | 全球变化的国际研究计划
科学计划与规划
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| Recommended Citation: | |
Selen Cremaschi. CAREER: Modeling and Optimization of Next Generation Feedstock Development for Chemical Process Industry. 2016-01-01.
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